READme.md

A database for document-storage/retrieval with automated curation
and structure discovery, so that documents may be efficiently organized
and queried not only based on human-labeled attributes/metadata, but also using
a variety of optional automatically-inferred latent features including:
semantics, topics, sentiment, eloquence, and entities of interest.

Inference of these properties is done using various statistical models and
NLP algorithms stored and run inside the database.

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What makes SemanticTextDB so cool?

We support augmented postgreSQL SELECT statments via the semanticSelect() API. This method provides you the power of cutting edge NLP
algorithms, with no additional coding. Its as easy as:

Using SemanticTextDB

Simply clone the repo and refer to SemanticTextDB_Tutorial.py for documentation.

With respect to viewing the tutorial, we STRONGLY recommend using iPython Notebook for viewing the SemanticTextDB_Tutorial.py.
Use SemanticTextDB_Tutorial.ipynb when viewing in ipython notebook. The experience is highly enhanced.